Martin Jullum

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 17

Top Topics

Predictive Model

Top Venues

Data Min. Knowl. Discov.

EXTRAAMAS@AAMAS

Publications

Lars Henry Berge Olsen, Ingrid Kristine Glad, Martin Jullum, Kjersti Aas
A comparative study of methods for estimating model-agnostic Shapley value explanations. Data Min. Knowl. Discov. 38 (4) (2024)
Annabelle Redelmeier, Martin Jullum, Kjersti Aas, Anders Løland
MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data. Data Min. Knowl. Discov. 38 (4) (2024)
Martin Jullum, Jacob Sjødin, Robindra Prabhu, Anders Løland
eXplego: An interactive Tool that Helps you Select Appropriate XAI-methods for your Explainability Needs. xAI (Late-breaking Work, Demos, Doctoral Consortium) (2023)
Fredrik Johannessen, Martin Jullum
Finding Money Launderers Using Heterogeneous Graph Neural Networks. CoRR (2023)
Lars Henry Berge Olsen, Ingrid Kristine Glad, Martin Jullum, Kjersti Aas
A Comparative Study of Methods for Estimating Conditional Shapley Values and When to Use Them. CoRR (2023)
Lars H. B. Olsen, Ingrid Kristine Glad, Martin Jullum, Kjersti Aas
Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features. J. Mach. Learn. Res. 23 (2022)
Lars Henry Berge Olsen, Ingrid Kristine Glad, Martin Jullum, Kjersti Aas
Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features. CoRR (2021)
Kjersti Aas, Thomas Nagler, Martin Jullum, Anders Løland
Explaining predictive models using Shapley values and non-parametric vine copulas. CoRR (2021)
Kary Främling, Marcus Westberg, Martin Jullum, Manik Madhikermi, Avleen Malhi
Comparison of Contextual Importance and Utility with LIME and Shapley Values. EXTRAAMAS@AAMAS (2021)
Kjersti Aas, Martin Jullum, Anders Løland
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values. Artif. Intell. 298 (2021)
Martin Jullum, Annabelle Redelmeier, Kjersti Aas
groupShapley: Efficient prediction explanation with Shapley values for feature groups. CoRR (2021)
Annabelle Redelmeier, Martin Jullum, Kjersti Aas, Anders Løland
MCCE: Monte Carlo sampling of realistic counterfactual explanations. CoRR (2021)
Dag Tjøstheim, Martin Jullum, Anders Løland
Statistical embedding: Beyond principal components. CoRR (2021)
Annabelle Redelmeier, Martin Jullum, Kjersti Aas
Explaining predictive models with mixed features using Shapley values and conditional inference trees. CoRR (2020)
Annabelle Redelmeier, Martin Jullum, Kjersti Aas
Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees. CD-MAKE (2020)
Kjersti Aas, Martin Jullum, Anders Løland
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values. CoRR (2019)
Nikolai Sellereite, Martin Jullum
shapr: An R-package for explaining machine learning models with dependence-aware Shapley values. J. Open Source Softw. 5 (46) (2019)